Occupational applicationsSince cobots (collaborative robots) are increasingly being introduced in industrial environments, being aware of their potential positive and negative impacts on human collaborators is essential. This study guides occupational health workers by identifying the potential gains (reduced perceived time demand, number of gestures and number of errors) and concerns (the cobot takes a long time to perceive its environment, which leads to an increased completion time) associated with working with cobots. In our study, the collaboration between human and cobot during an assembly task did not negatively impact perceived cognitive load, increased completion time (but decreased perceived time demand), and decreased the number of gestures performed by participants and the number of errors made. Thus, performing the task in collaboration with a cobot improved the user's experience and performance, except for completion time, which increased.This study opens up avenues to investigate how to improve cobots to ensure the usability of the human-machine system at work.

In this paper, we address flexible assembly plans generation to accommodate human task variability. Unlike existing approaches, the proposed approach is based on a free-style human-robot interaction (HRI) that does not impose any task order on the participants and furthermore can accommodate their errors and help them to correct the errors without stopping the whole assembly process. Our approach is implemented in a real robotic architecture that combines sensory-motor modules with Hierarchical Task Networks (HTN) to endow the cobot with the necessary adaptability to correspond to human actions dynamically. We show experimentally with 56 participants on a simulated industrial assembly task that the cobot increases the task performance (reduction in the number of errors and gestures) without increasing the participants' cognitive load.